Integrated Use of Biochemical, Native Mass Spectrometry, Computational, and Genome-Editing Methods to Elucidate the Mechanism of a Salmonella deglycase

Optimizing glycation control in diabetes: An integrated approach for inhibiting nonenzymatic glycation reactions of biological macromolecules

Diabetes is a multifactorial disorder that increases mortality and disability due to its complications. A key driver of these complications is nonenzymatic glycation, which generates advanced glycation end-products (AGEs) that impair tissue function. Therefore, effective nonenzymatic glycation prevention and control strategies are urgently needed. This review comprehensively describes the molecular mechanisms and pathological consequences of nonenzymatic glycation in diabetes and outlines various anti-glycation strategies, such as lowering plasma glucose, interfering with the glycation reaction, and degrading early and late glycation products. Diet, exercise, and hypoglycemic medications can reduce the onset of high glucose at the source. Glucose or amino acid analogs such as flavonoids, lysine and aminoguanidine competitively bind to proteins or glucose to block the initial nonenzymatic glycation reaction. In addition, deglycation enzymes such as amadoriase, fructosamine-3-kinase, parkinson's disease protein, glutamine amidotransferase-like class 1 domain-containing 3A and terminal FraB deglycase can eliminate existing nonenzymatic glycation products. These strategies involve nutritional, pharmacological, and enzymatic interventions that target different stages of nonenzymatic glycation. This review also emphasizes the therapeutic potential of anti-glycation drugs for preventing and treating diabetes complications.

Identification of Small-Molecule Inhibitors of the Salmonella FraB Deglycase Using a Live-Cell Assay

Nontyphoidal salmonellosis is one of the most significant foodborne diseases in the United States and globally. There are no vaccines available for human use to prevent this disease, and only broad-spectrum antibiotics are available to treat complicated cases of the disease. However, antibiotic resistance is on the rise and new therapeutics are needed. We previously identified the Salmonella fraB gene, that mutation of causes attenuation of fitness in the murine gastrointestinal tract. The FraB gene product is encoded in an operon responsible for the uptake and utilization of fructose-asparagine (F-Asn), an Amadori product found in several human foods. Mutations in fraB cause an accumulation of the FraB substrate, 6-phosphofructose-aspartate (6-P-F-Asp), which is toxic to Salmonella. The F-Asn catabolic pathway is found only in the nontyphoidal Salmonella serovars, a few Citrobacter and Klebsiella isolates, and a few species of Clostridium; it is not found in humans. Thus, targeting FraB with novel antimicrobials is expected to be Salmonella specific, leaving the normal microbiota largely intact and having no effect on the host. We performed high-throughput screening (HTS) to identify small-molecule inhibitors of FraB using growth-based assays comparing a wild-type Salmonella and a Δfra island mutant control. We screened 224,009 compounds in duplicate. After hit triage and validation, we found three compounds that inhibit Salmonella in an fra-dependent manner, with 50% inhibitory concentration (IC50) values ranging from 89 to 150 μM. Testing these compounds with recombinant FraB and synthetic 6-P-F-Asp confirmed that they are uncompetitive inhibitors of FraB with Ki' (inhibitor constant) values ranging from 26 to 116 μM. IMPORTANCE Nontyphoidal salmonellosis is a serious threat in the United States and globally. We have recently identified an enzyme, FraB, that when mutated renders Salmonella growth defective in vitro and unfit in mouse models of gastroenteritis. FraB is quite rare in bacteria and is not found in humans or other animals. Here, we have identified small-molecule inhibitors of FraB that inhibit the growth of Salmonella. These could provide the foundation for a therapeutic to reduce the duration and severity of Salmonella infections.

Serendipitous Discovery of a Competitive Inhibitor of FraB, a Salmonella Deglycase and Drug Target

Although salmonellosis, an infectious disease, is a significant global healthcare burden, there are no Salmonella-specific vaccines or therapeutics for humans. Motivated by our finding that FraB, a Salmonella deglycase responsible for fructose-asparagine catabolism, is a viable drug target, we initiated experimental and computational efforts to identify inhibitors of FraB. To this end, our recent high-throughput screening initiative yielded almost exclusively uncompetitive inhibitors of FraB. In parallel with this advance, we report here how a separate structural and computational biology investigation of FrlB, a FraB paralog, led to the serendipitous discovery that 2-deoxy-6-phosphogluconate is a competitive inhibitor of FraB (KI ~ 3 μM). However, this compound was ineffective in inhibiting the growth of Salmonella in a liquid culture. In addition to poor uptake, cellular metabolic transformations by a Salmonella dehydrogenase and different phosphatases likely undermined the efficacy of 2-deoxy-6-phosphogluconate in live-cell assays. These insights inform our ongoing efforts to synthesize non-hydrolyzable/-metabolizable analogs of 2-deoxy-6-phosphogluconate. We showcase our findings largely to (re)emphasize the role of serendipity and the importance of multi-pronged approaches in drug discovery.

Surface-induced Dissociation Mass Spectrometry as a Structural Biology Tool

Native mass spectrometry (nMS) is evolving into a workhorse for structural biology. The plethora of online and offline preparation, separation, and purification methods as well as numerous ionization techniques combined with powerful new hybrid ion mobility and mass spectrometry systems has illustrated the great potential of nMS for structural biology. Fundamental to the progression of nMS has been the development of novel activation methods for dissociating proteins and protein complexes to deduce primary, secondary, tertiary, and quaternary structure through the combined use of multiple MS/MS technologies. This review highlights the key features and advantages of surface collisions (surface-induced dissociation, SID) for probing the connectivity of subunits within protein and nucleoprotein complexes and, in particular, for solving protein structure in conjunction with complementary techniques such as cryo-EM and computational modeling. Several case studies highlight the significant role SID, and more generally nMS, will play in structural elucidation of biological assemblies in the future as the technology becomes more widely adopted. Cases are presented where SID agrees with solved crystal or cryoEM structures or provides connectivity maps that are otherwise inaccessible by "gold standard" structural biology techniques.

Characterization of a Salmonella transcription factor-DNA complex and identification of the inducer by native mass spectrometry

FraR, a transcriptional repressor, was postulated to regulate the metabolism of the Amadori compound fructose-asparagine (F-Asn) in the foodborne pathogen Salmonella enterica. Here, the DNA- and inducer-binding affinities and stoichiometries of FraR were determined and cross-validated by electrophoretic mobility-shift assays (EMSAs) and online buffer exchange coupled to native mass spectrometry (OBE-nMS). We demonstrate the utility of OBE-nMS to characterize protein and protein-DNA complexes that are not amenable to offline exchange into volatile buffers. OBE-nMS complemented EMSAs by revealing that FraR binds to the operator DNA as a dimer and by establishing 6-phosphofructose-aspartate as the inducer that weakens DNA binding by FraR. These results provide insights into how FraR regulates the expression of F-Asn-catabolizing enzymes and add to our understanding of the intricate bacterial circuitry that dictates utilization of diverse nutrients.

Sugar-Phosphate Toxicities

Accumulation of phosphorylated intermediates during cellular metabolism can have wide-ranging toxic effects on many organisms, including humans and the pathogens that infect them. These toxicities can be induced by feeding an upstream metabolite (a sugar, for instance) while simultaneously blocking the appropriate metabolic pathway with either a mutation or an enzyme inhibitor. Here, we survey the toxicities that can arise in the metabolism of glucose, galactose, fructose, fructose-asparagine, glycerol, trehalose, maltose, mannose, mannitol, arabinose, and rhamnose. Select enzymes in these metabolic pathways may serve as novel therapeutic targets. Some are conserved broadly among prokaryotes and eukaryotes (e.g., glucose and galactose) and are therefore unlikely to be viable drug targets. However, others are found only in bacteria (e.g., fructose-asparagine, rhamnose, and arabinose), and one is found in fungi but not in humans (trehalose). We discuss what is known about the mechanisms of toxicity and how resistance is achieved in order to identify the prospects and challenges associated with targeted exploitation of these pervasive metabolic vulnerabilities.

Analysis of Tagged Proteins Using Tandem Affinity-Buffer Exchange Chromatography Online with Native Mass Spectrometry

Protein overexpression and purification are critical for in vitro structure-function characterization studies. However, some proteins are difficult to express in heterologous systems due to host-related (e.g., codon usage, translation rate) and/or protein-specific (e.g., toxicity, aggregation) challenges. Therefore, it is often necessary to test multiple overexpression and purification conditions to maximize the yield of functional protein, particularly for resource-heavy downstream applications (e.g., biocatalysts, tertiary structure determination, biotherapeutics). Here, we describe an automatable liquid chromatography-mass spectrometry-based method for direct analysis of target proteins in cell lysates. This approach is facilitated by coupling immobilized metal affinity chromatography (IMAC), which leverages engineered poly-histidine tags in proteins of interest, with size exclusion-based online buffer exchange (OBE) and native mass spectrometry (nMS). While we illustrate a proof of concept here using relatively straightforward examples, the use of IMAC-OBE-nMS to optimize conditions for large-scale protein production may become invaluable for expediting structural biology and biotherapeutic initiatives.

Protein Structure Prediction from NMR Hydrogen-Deuterium Exchange Data

Amide hydrogen-deuterium exchange (HDX) has long been used to determine regional flexibility and binding sites in proteins; however, the data are too sparse for full structural characterization. Experiments that measure HDX rates, such as HDX-NMR, have far higher throughput compared to structure determination via X-ray crystallography, cryo-EM, or a full suite of NMR experiments. Data from HDX-NMR experiments encode information on the protein structure, making HDX a prime candidate to be supplemented by computational algorithms for protein structure prediction. We have developed a methodology to incorporate HDX-NMR data into ab initio protein structure prediction using the Rosetta software framework to predict structures based on experimental agreement. To demonstrate the efficacy of our algorithm, we examined 38 proteins with HDX-NMR data available, comparing the predicted model with and without the incorporation of HDX data into scoring. The root-mean-square deviation (rmsd, a measure of the average atomic distance between superimposed models) of the predicted model improved by 1.42 Å on average after incorporating the HDX-NMR data into scoring. The average rmsd improvement for the proteins where the selected model rmsd changed after incorporating HDX data was 3.63 Å, including one improvement of more than 11 Å and seven proteins improving by greater than 4 Å, with 12/15 proteins improving overall. Additionally, for independent verification, two proteins that were not part of the original benchmark were scored including HDX data, with a dramatic improvement of the selected model rmsd of nearly 9 Å for one of the proteins. Moreover, we have developed a confidence metric allowing us to successfully identify near-native models in the absence of a native structure. Improvement in model selection with a strong confidence measure demonstrates that protein structure prediction with HDX-NMR is a powerful tool which can be performed with minimal additional computational strain and expense.